Application of ordered-subsets expectation-maximization (OSEM) algorithm to cone-beam SPECT for accelerated 3D reconstruction

We investigated the performance of an ordered-subsets expectation-maximization (OSEM) algorithm for accelerated reconstruction in cone-beam SPECT. SPECT scans were performed using a Defrise phantom filled with 0.9 mu Ci/ml of Tc-99m and a dual-head gamma camera equipped with one cone-beam (CBC, f = 70 cm) and one parallel-beam collimator (PBC). Images were reconstructed using a fully-3D approach with resolution and attenuation modeling and an ordered-subsets version of a maximum-likelihood expectation-maximization algorithm (MLEM). Three grouping patterns of subsets were applied: consecutive, orthogonal, and uniform. In contrast to PBC SPECT, we observe that, in CBC SPECT, the reconstruction grouping pattern of the subsets is very important for the image quality obtained. Only when the projection data grouped into a subset were selected as uniformly as possible from all the acquired views, were the image quality and the noise in the images very close to results obtained using MLEM. However, we note that, for both CBC and PBC SPECT, the loglikelihood for a given iteration is practically the same for different grouping patterns of subsets.